Bootstrap is a derivation of Monte Carlo technique introduced by Efron in 1979. It uses the re-sampling with replacement method (unlike the re-sampling with no replacement method that we used in the Lotto Number Generator example). It is a convenient tool to extract estimates (such as standard deviation and confident interval) from a non-parametric data set (a data set with no underling distribution is assumed) or estimates that do not have a closed form (cannot be expressed in an equation)..
See Examples below;
Standard Deviation and Mean
Lotto Number Generator >
Playing Card Probability >
Normal Distribution Random Number Generator >
Monte Carlo Integration >
Black-Scholes Option Pricing Model - European Call and Put >
Binomial Option Pricing Model >
Portfolio Optimization >
Multiple Regression >
Bootstrap - A Non-Parametric Approach >
Multivariate Standard Normal Probability Distribution >
Monte Carlo Simulation >
Option Greeks Based on Black-Scholes Option Pricing Model.
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